OpenRaiser/Intern-Atlas huggingface dataset:
Temporal Analysis of Language through Neural Language Models
Venue: arXiv cs.CL 2014
Year: 2014

We provide a method for automatically detecting change in language across time through a chronologically trained neural language model. We train the model on the Google Books Ngram corpus to obtain word vector representations specific to each year, and identify words that have changed significantly from 1900 to 2009. The model identifies words such as "cell" and "gay" as having changed during that time period. The model simultaneously identifies the specific years during which such words underwent change.
Credibility Adjusted Term Frequency: A Supervised Term Weighting Scheme for Sentiment Analysis and Text Classification
Venue: arXiv cs.CL 2014
Year: 2014

We provide a simple but novel supervised weighting scheme for adjusting term frequency in tf-idf for sentiment analysis and text classification. We compare our method to baseline weighting schemes and find that it outperforms them on multiple benchmarks. The method is robust and works well on both snippets and longer documents.
A Linear Logic Programming Language for Concurrent Programming over Graph Structures
Venue: arXiv cs.PL 2014
Year: 2014

We have designed a new logic programming language called LM (Linear Meld) for programming graph-based algorithms in a declarative fashion. Our language is based on linear logic, an expressive logical system where logical facts can be consumed. Because LM integrates both classical and linear logic, LM tends to be more expressive than other logic programming languages. LM programs are naturally concurrent because facts are partitioned by nodes of a graph data structure. Computation is performed at the node level while communication happens between connected nodes. In this paper, we present the syntax and operational semantics of our language and illustrate its use through a number of examples.
Dynamic Consistency Checking in Goal-Directed Answer Set Programming
Venue: arXiv cs.LO 2014
Year: 2014

In answer set programming, inconsistencies arise when the constraints placed on a program become unsatisfiable. In this paper, we introduce a technique for dynamic consistency checking for our goal-directed method for computing answer sets, under which only those constraints deemed relevant to the partial answer set are tested, allowing inconsistent knowledgebases to be successfully queried. However, the algorithm guarantees that, if a program has at least one consistent answer set, any partial answer set returned will be a subset of some consistent answer set. To appear in Theory and Practice of Logic Programming (TPLP).
Vicious Circle Principle and Logic Programs with Aggregates
Venue: arXiv cs.AI 2014
Year: 2014

The paper presents a knowledge representation language $\mathcal{A}log$ which extends ASP with aggregates. The goal is to have a language based on simple syntax and clear intuitive and mathematical semantics. We give some properties of $\mathcal{A}log$, an algorithm for computing its answer sets, and comparison with other approaches.
Abstract Diagnosis for tccp using a Linear Temporal Logic
Venue: arXiv cs.PL 2014
Year: 2014

Automatic techniques for program verification usually suffer the well-known state explosion problem. Most of the classical approaches are based on browsing the structure of some form of model (which represents the behavior of the program) to check if a given specification is valid. This implies that a part of the model has to be built, and sometimes the needed fragment is quite huge. In this work, we provide an alternative automatic decision method to check whether a given property, specified in a linear temporal logic, is valid w.r.t. a tccp program. Our proposal (based on abstract interpretation techniques) does not require to build any model at all. Our results guarantee correctness but, as usual when using an abstract semantics, completeness is lost.
Improving Physical-Layer Security in Wireless Communications Using Diversity Techniques
Venue: arXiv cs.IT 2014
Year: 2014

Due to the broadcast nature of radio propagation, the wireless transmission can be readily overheard by unauthorized users for interception purposes and is thus highly vulnerable to eavesdropping attacks. To this end, physical-layer security is emerging as a promising paradigm to protect the wireless communications against eavesdropping attacks by exploiting the physical characteristics of wireless channels. This article is focused on the investigation of diversity techniques to improve the physical-layer security, differing from the conventional artificial noise generation and beamforming techniques which typically consume additional power for generating artificial noise and exhibit high implementation complexity for beamformer design. We present several diversity approaches to improve the wireless physical-layer security, including the multiple-input multiple-output (MIMO), multiuser diversity, and cooperative diversity. To illustrate the security improvement through diversity, we propose a case study of exploiting cooperative relays to assist the signal transmission from source to destination while defending against eavesdropping attacks. We evaluate the security performance of cooperative relay transmission in Rayleigh fading environments in terms of secrecy capacity and intercept probability. It is shown that as the number of relays increases, the secrecy capacity and intercept probability of the cooperative relay transmission both improve significantly, implying the advantage of exploiting cooperative diversity to improve the physical-layer security against eavesdropping attacks.
Topic words analysis based on LDA model
Venue: arXiv cs.SI 2014
Year: 2014

Social network analysis (SNA), which is a research field describing and modeling the social connection of a certain group of people, is popular among network services. Our topic words analysis project is a SNA method to visualize the topic words among emails from Obama.com to accounts registered in Columbus, Ohio. Based on Latent Dirichlet Allocation (LDA) model, a popular topic model of SNA, our project characterizes the preference of senders for target group of receptors. Gibbs sampling is used to estimate topic and word distribution. Our training and testing data are emails from the carbon-free server Datagreening.com. We use parallel computing tool BashReduce for word processing and generate related words under each latent topic to discovers typical information of political news sending specially to local Columbus receptors. Running on two instances using paralleling tool BashReduce, our project contributes almost 30% speedup processing the raw contents, comparing with processing contents on one instance locally. Also, the experimental result shows that the LDA model applied in our project provides precision rate 53.96% higher than TF-IDF model finding target words, on the condition that appropriate size of topic words list is selected.
Complex Networks Measures for Differentiation between Normal and Shuffled Croatian Texts
Venue: arXiv cs.CL 2014
Year: 2014

This paper studies the properties of the Croatian texts via complex networks. We present network properties of normal and shuffled Croatian texts for different shuffling principles: on the sentence level and on the text level. In both experiments we preserved the vocabulary size, word and sentence frequency distributions. Additionally, in the first shuffling approach we preserved the sentence structure of the text and the number of words per sentence. Obtained results showed that degree rank distributions exhibit no substantial deviation in shuffled networks, and strength rank distributions are preserved due to the same word frequencies. Therefore, standard approach to study the structure of linguistic co-occurrence networks showed no clear difference among the topologies of normal and shuffled texts. Finally, we showed that the in- and out- selectivity values from shuffled texts are constantly below selectivity values calculated from normal texts. Our results corroborate that the node selectivity measure can capture structural differences between original and shuffled Croatian texts.
Allocation des ressources radio en LTE
Venue: arXiv cs.NI 2014
Year: 2014

In this paper we investigate several approaches and algorithms that have been proposed in the literature to address the need (allocate resources efficiently), this diversity and multitude of algorithms is related the factors considered for the optimal management of requested radio traffic type resource, specifically the requested QoS by the EU.
On the Topology Maintenance of Dynamic P2P Overlays through Self-Healing Local Interactions
Venue: arXiv cs.NI 2014
Year: 2014

This paper deals with the use of self-organizing protocols to improve the reliability of dynamic Peer-to-Peer (P2P) overlay networks. We present two approaches, that employ local knowledge of the 2nd neighborhood of nodes. The first scheme is a simple protocol requiring interactions among nodes and their direct neighbors. The second scheme extends this approach by resorting to the Edge Clustering Coefficient (ECC), a local measure that allows to identify those edges that connect different clusters in an overlay. A simulation assessment is presented, which evaluates these protocols over uniform networks, clustered networks and scale-free networks. Different failure modes are considered. Results demonstrate the viability of the proposal.
Personalized recommendation with corrected similarity
Venue: arXiv cs.IR 2014
Year: 2014

Personalized recommendation attracts a surge of interdisciplinary researches. Especially, similarity based methods in applications of real recommendation systems achieve great success. However, the computations of similarities are overestimated or underestimated outstandingly due to the defective strategy of unidirectional similarity estimation. In this paper, we solve this drawback by leveraging mutual correction of forward and backward similarity estimations, and propose a new personalized recommendation index, i.e., corrected similarity based inference (CSI). Through extensive experiments on four benchmark datasets, the results show a greater improvement of CSI in comparison with these mainstream baselines. And the detailed analysis is presented to unveil and understand the origin of such difference between CSI and mainstream indices.
3DNA: A Tool for DNA Sculpting
Venue: arXiv cs.ET 2014
Year: 2014

DNA self-assembly is a robust and programmable approach for building structures at nanoscale. Researchers around the world have proposed and implemented different techniques to build two dimensional and three dimensional nano structures. One such technique involves the implementation of DNA Bricks proposed by Ke et al., 2012 to create complex three-dimensional (3D) structures. Modeling these DNA nano structures can prove to be a cumbersome and tedious task. Exploiting the programmability of base-pairing to produce self-assembling custom shapes, we present a software suite 3DNA, which can be used for modeling, editing and visualizing such complex structures. 3DNA is an open source software which works on the simple and modular self assembly of DNA Bricks, offering a more intuitive better approach for constructing 3D shapes. Apart from modeling and envisaging shapes through a simple graphical user interface, 3DNA also supports an integrated random sequence generator that generates DNA sequences corresponding to the designed model. The software is available at www.guptalab.org/3dna
On Energy-efficiency in Wireless Networks: A Game-theoretic Approach to Cooperation Inspired by Evolutionary Biology
Venue: arXiv cs.NI 2014
Year: 2014

We develop a game-theoretic framework to investigate the effect of cooperation on the energy efficiency in wireless networks. We address two examples of network architectures, resembling ad-hoc network and network with central infrastructure node. Most present approaches address the issue of energy efficiency in communication networks by using complex algorithms to enforce cooperation in the network, followed by extensive signal processing at the network nodes. Instead, we address cooperative communication scenarios which are governed by simple, evolutionary-like, local rules, and do not require strategic complexity of the network nodes. The approach is motivated by recent results in evolutionary biology which suggest that cooperation can emerge in Nature by evolution, i. e. can be favoured by natural selection, if certain mechanism is at work. As result, we are able to show by experiments that cooperative behavior can indeed emerge and persist in wireless networks, even if the behavior of the individual nodes is driven by selfish decision making. The results from this work indicate that uncomplicated local rules, followed by simple fitness evaluation, can promote cooperation and generate network behavior which yields global energy efficiency in certain wireless networks.
Empirical Study of Artificial Fish Swarm Algorithm
Venue: arXiv cs.AI 2014
Year: 2014

Artificial fish swarm algorithm (AFSA) is one of the swarm intelligence optimization algorithms that works based on population and stochastic search. In order to achieve acceptable result, there are many parameters needs to be adjusted in AFSA. Among these parameters, visual and step are very significant in view of the fact that artificial fish basically move based on these parameters. In standard AFSA, these two parameters remain constant until the algorithm termination. Large values of these parameters increase the capability of algorithm in global search, while small values improve the local search ability of the algorithm. In this paper, we empirically study the performance of the AFSA and different approaches to balance between local and global exploration have been tested based on the adaptive modification of visual and step during algorithm execution. The proposed approaches have been evaluated based on the four well-known benchmark functions. Experimental results show considerable positive impact on the performance of AFSA.
Security concerns of ipv6-slaac and security policies to diminish the risk associated with them
Venue: arXiv cs.CR 2014
Year: 2014

Though, IPv6 has presented a long list of features that will actually change the entire networking environment, it still represents a very small proportion of Internet traffic. One of the major reasons behind its partial acceptance is its security, as these features were incorporated in IPv6 just to enhance its overall performance and quality of service, thereby neglecting its security part. One such feature is Stateless Address Auto Configuration or simply SLAAC, which have undoubtedly reduced a lot of overhead in configuring networks, but on the same time it has challenged the security of IPv6 networks. This research work, therefore targets at proposing some security policies to mitigate the risks associated with SLAAC, by understanding its working scenario and trying to create the possible attack vector to highlight its security concerns. Hence, the implementation of these policies will directly add security to networks and make them resistant to SLAAC based attacks.
Les mathématiques de la langue : l'approche formelle de Montague
Venue: arXiv cs.CL 2014
Year: 2014

We present a natural language modelization method which is strongely relying on mathematics. This method, called "Formal Semantics," has been initiated by the American linguist Richard M. Montague in the 1970's. It uses mathematical tools such as formal languages and grammars, first-order logic, type theory and $λ$-calculus. Our goal is to have the reader discover both Montagovian formal semantics and the mathematical tools that he used in his method. ----- Nous présentons une méthode de modélisation de la langue naturelle qui est fortement basée sur les mathématiques. Cette méthode, appelée «sémantique formelle», a été initiée par le linguiste américain Richard M. Montague dans les années 1970. Elle utilise des outils mathématiques tels que les langages et grammaires formels, la logique du 1er ordre, la théorie de types et le $λ$-calcul. Nous nous proposons de faire découvrir au lecteur tant la sémantique formelle de Montague que les outils mathématiques dont il s'est servi.
Spreading processes in Multilayer Networks
Venue: arXiv cs.SI 2014
Year: 2014

Several systems can be modeled as sets of interconnected networks or networks with multiple types of connections, here generally called multilayer networks. Spreading processes such as information propagation among users of an online social networks, or the diffusion of pathogens among individuals through their contact network, are fundamental phenomena occurring in these networks. However, while information diffusion in single networks has received considerable attention from various disciplines for over a decade, spreading processes in multilayer networks is still a young research area presenting many challenging research issues. In this paper we review the main models, results and applications of multilayer spreading processes and discuss some promising research directions.
Partitioning Networks with Node Attributes by Compressing Information Flow
Venue: arXiv cs.SI 2014
Year: 2014

Real-world networks are often organized as modules or communities of similar nodes that serve as functional units. These networks are also rich in content, with nodes having distinguishing features or attributes. In order to discover a network's modular structure, it is necessary to take into account not only its links but also node attributes. We describe an information-theoretic method that identifies modules by compressing descriptions of information flow on a network. Our formulation introduces node content into the description of information flow, which we then minimize to discover groups of nodes with similar attributes that also tend to trap the flow of information. The method has several advantages: it is conceptually simple and does not require ad-hoc parameters to specify the number of modules or to control the relative contribution of links and node attributes to network structure. We apply the proposed method to partition real-world networks with known community structure. We demonstrate that adding node attributes helps recover the underlying community structure in content-rich networks more effectively than using links alone. In addition, we show that our method is faster and more accurate than alternative state-of-the-art algorithms.
Bipedal Model Based on Human Gait Pattern Parameters for Sagittal Plane Movement
Venue: arXiv cs.RO 2014
Year: 2014

The present research as described in this paper tries to impart how imitation based learning for behavior-based programming can be used to teach the robot. This development is a big step in way to prove that push recovery is a software engineering problem and not hardware engineering problem. The walking algorithm used here aims to select a subset of push recovery problem i.e. disturbance from environment. We applied the physics at each joint of Halo with some degree of freedom. The proposed model, Halo is different from other models as previously developed model were inconsistent with data for different persons. This would lead to development of the generalized biped model in future and will bridge the gap between performance and inconsistency. In this paper the proposed model is applied to data of different persons. Accuracy of model, performance and result is measured using the behavior negotiation capability of model developed. In order to improve the performance, proposed model gives the freedom to handle each joint independently based on the belongingness value for each joint. The development can be considered as important development for future world of robotics. The accuracy of model is 70% in one go.
Real Time Object Tracking Based on Inter-frame Coding: A Review
Venue: arXiv cs.CV 2014
Year: 2014

Inter-frame Coding plays significant role for video Compression and Computer Vision. Computer vision systems have been incorporated in many real life applications (e.g. surveillance systems, medical imaging, robot navigation and identity verification systems). Object tracking is a key computer vision topic, which aims at detecting the position of a moving object from a video sequence. The application of Inter-frame Coding for low frame rate video, as well as for low resolution video. Various methods based on Top-down approach just like kernel based or mean shift technique are used to track the object for video, So, Inter-frame Coding algorithms are widely adopted by video coding standards, mainly due to their simplicity and good distortion performance for object tracking.
User-Centric Intercell Interference Nulling for Downlink Small Cell Networks
Venue: arXiv cs.IT 2014
Year: 2014

Small cell networks are regarded as a promising candidate to meet the exponential growth of mobile data traffic in cellular networks. With a dense deployment of access points, spatial reuse will be improved, and uniform coverage can be provided. However, such performance gains cannot be achieved without effective intercell interference management. In this paper, a novel interference coordination strategy, called user-centric intercell interference nulling, is proposed for small cell networks. A main merit of the proposed strategy is its ability to effectively identify and mitigate the dominant interference for each user. Different from existing works, each user selects the coordinating base stations (BSs) based on the relative distance between the home BS and the interfering BSs, called the interference nulling (IN) range, and thus interference nulling adapts to each user's own interference situation. By adopting a random spatial network model, we derive an approximate expression of the successful transmission probability to the typical user, which is then used to determine the optimal IN range. Simulation results shall confirm the tightness of the approximation, and demonstrate significant performance gains (about 35%-40%) of the proposed coordination strategy, compared with the non-coordination case. Moreover, it is shown that the proposed strategy outperforms other interference nulling methods. Finally, the effect of imperfect channel state information (CSI) is investigated, where CSI is assumed to be obtained via limited feedback. It is shown that the proposed coordination strategy still provides significant performance gains even with a moderate number of feedback bits.
Peacock: Learning Long-Tail Topic Features for Industrial Applications
Venue: arXiv cs.IR 2014
Year: 2014

Latent Dirichlet allocation (LDA) is a popular topic modeling technique in academia but less so in industry, especially in large-scale applications involving search engine and online advertising systems. A main underlying reason is that the topic models used have been too small in scale to be useful; for example, some of the largest LDA models reported in literature have up to $10^3$ topics, which cover difficultly the long-tail semantic word sets. In this paper, we show that the number of topics is a key factor that can significantly boost the utility of topic-modeling systems. In particular, we show that a "big" LDA model with at least $10^5$ topics inferred from $10^9$ search queries can achieve a significant improvement on industrial search engine and online advertising systems, both of which serving hundreds of millions of users. We develop a novel distributed system called Peacock to learn big LDA models from big data. The main features of Peacock include hierarchical distributed architecture, real-time prediction and topic de-duplication. We empirically demonstrate that the Peacock system is capable of providing significant benefits via highly scalable LDA topic models for several industrial applications.